Develop High-Performance GPU Kernels in C++ with NVIDIA CUDA Tile | NVIDIA Technical Blog

What this post added

Introduces CUDA Tile C++, enabling developers to write tile-based GPU kernels directly in C++ within existing codebases. This abstracts low-level parallelism, memory movement, and hardware features, allowing for more declarative kernel expressions compared to the SIMT model. It details vector addition and matrix multiplication examples, highlighting the use of tensor spans, partition views, and tile operations. The post also covers performance considerations like `__restrict__` and alignment, and mentions profiling with Nsight Compute.